All Tags
AWS
algorithm-design
architecture
cloud-principles
cost-reduction
data-centric
data-compression
data-processing
deployment
design
edge-computing
energy-footprint
hardware
libraries
locality
machine-learning
management
measured
migration
model-optimization
model-training
performance
queries
rebuilding
scaling
services
strategies
template
workloads
Tactic: Compress infrequently accessed data
Tactic sort:
Awesome Tactic
Type: Architectural Tactic
Category: resource-adaptation
Tags:
data-compression
Title
Compress infrequently accessed data
Description
Data that is used infrequently should be compressed to optimize the storage costs. In contrast, data that is more frequently accessed might not be efficient to compress as the CPU power that is required to compress and extract the data might cost more than the costs saved of storing a smaller volume of data. Understanding the exact threshold to compress the data depends on the underlying hardware and can be defined through experimentation. Compressing large amounts of data that are not frequently accessed can result in major cost savings. In this case, we expect a correlation between cost and energy savings. Whenever less data is stored, less energy is used for storage. The only trade-off that needs to be considered is the amount of energy that is required to (de)compress the data
Participant
Cloud consumer
Related software artifact
Data resources
Context
Public cloud
Software feature
Storage
Tactic intent
Applying data compression to optimize storage costs
Target quality attribute
Cost-efficiency
Other related quality attributes
Energy-efficiency
Measured impact
< unknown >